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Probabilistic Image Processing Theory Considering Image Structure

Research Project

Project/Area Number 18K18120
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 61040:Soft computing-related
Research InstitutionOtaru University of Commerce

Principal Investigator

Kataoka Shun  小樽商科大学, 商学部, 准教授 (50737278)

Project Period (FY) 2018-04-01 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywords確率的画像処理 / 確率的グラフィカルモデル / マルコフ確率場 / EMアルゴリズム / 統計的機械学習理論 / ソフトコンピューティング / 確率的情報処理 / 画像処理
Outline of Final Research Achievements

In this project, we consider the fusion of probabilistic image processing and machine learning. The main difficulty of applying machine learning concept to probabilistic image processing is a size of the dataset. Many machine learning methods assume a large data set, but the data in image processing is only one image to be processed. Therefore, we consider the method that converts machine learning result into a probabilistic image processing method.

Academic Significance and Societal Importance of the Research Achievements

本研究計画では確率的画像処理の機械学習の融合について取り組んだ。機械学習の方法は深層学習の方法を中心に様々な分野で成果を挙げているが、機械学習の問題設定を他の分野にそのまま持ち込んだ形が多く、機械学習の考え方の取り入れて分野を発展させていく取り組みはそこまで多くは行われていない。本研究で得られた結果は、機械学習の方法を画像処理に直接適用するのではなく、機械学習の考え方を画像処理の分野に応用する一つの例として今後の確率的画像処理分野の発展に貢献するものと考えている。

Report

(5 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (5 results)

All 2020 2019 2018

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (3 results) (of which Int'l Joint Research: 1 results,  Invited: 2 results) Book (1 results)

  • [Journal Article] Bayesian Image Denoising with Multiple Noisy Images2019

    • Author(s)
      Shun Kataoka and Muneki Yasuda
    • Journal Title

      The Review of Socionetwork Strategies

      Volume: 13 Issue: 2 Pages: 267-280

    • DOI

      10.1007/s12626-019-00043-3

    • NAID

      120006767844

    • Related Report
      2019 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] 確率的情報処理への統計物理学的手法の応用2020

    • Author(s)
      片岡 駿
    • Organizer
      電子情報通信学会2020年総合大会
    • Related Report
      2019 Research-status Report
    • Invited
  • [Presentation] Neural network and its variants2019

    • Author(s)
      Shun Kataoka
    • Organizer
      The 34th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2019)
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] 機械学習結果を利用した確率的情報処理法に関する一検討2019

    • Author(s)
      片岡 駿
    • Organizer
      システム数理と応用研究会
    • Related Report
      2018 Research-status Report
  • [Book] 画像処理の統計モデリング2018

    • Author(s)
      片岡 駿、大関 真之、安田 宗樹、田中 和之、照井 伸彦、小谷 元子、赤間 陽二、花輪 公雄
    • Total Pages
      264
    • Publisher
      共立出版
    • ISBN
      9784320111233
    • Related Report
      2018 Research-status Report

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Published: 2018-04-23   Modified: 2023-01-30  

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